When a technology's average daily usage surges 1,400-fold within 26 months, it ceases to be merely a technology. The token—the fundamental unit measuring intelligent services, emerging from large language models—is penetrating every corner of the national economy at an unprecedented pace, reshaping the underlying logic of value creation, industrial organization, and daily life. Confronting this explosive growth, two critical questions demand answers: 1. How can markets profit from it? 2. How should nations respond?
A recent discussion on token economics offered insightful responses to the first question. It defined "token economics" from an industrial economic system perspective, outlining this emerging new economic framework across value, production, and demand dimensions. This analysis accurately addressed market uncertainties, explaining new business models, pricing strategies, and competitive landscapes. Another study systematically analyzed tokens as a unique factor of production with special economic attributes, raising scattered theoretical and policy questions. However, tokens represent far more than just a special data-type production factor. They are a rapidly evolving phenomenon with profound impacts, fundamentally altering our production methods and lifestyles. While markets focus on profitability, policymakers must proactively address potential deep-seated challenges.
This article shifts the focus of token economy research from "market" concerns to "governance" considerations, emphasizing holistic and systematic analysis. Initial attempts to apply existing economic theories to token economy impacts on micro-level individual behavior, macroeconomic operations, and national governance systems revealed a fundamental dilemma: classical theories born from industrial or early information economies often prove inadequate or partially ineffective when explaining this intelligent-era innovation. For instance, token value cannot be simply measured by "cost" or "socially necessary labor time" since production and consumption occur simultaneously. Its L-shaped cost structure challenges traditional firm theories. It simultaneously creates "service deflation" and "computing power inflation," creating monetary policy dilemmas. It may catalyze new production relationships based on "intelligent access rights."
Rather than forcing old frameworks onto new realities, the urgent task involves creating a new map filled with question marks. This article positions itself as foundational work—not providing answers but systematically posing the right questions. It aims to construct an analytical framework identifying tokens as unique entities with "instant unity of production and consumption," revealing fundamental contradictions along the "micro-foundations → macro-manifestations → governance responses" chain that existing theories struggle to explain but which impact future national welfare. Clearly articulating these questions provides essential direction for subsequent theoretical innovation, empirical research, and strategic policy design.
I. Micro-Foundations: Value, Production and Organizational Theory Consuming tokens resembles using "intelligent electricity"—paying per unit to power large models. But this superficial analogy collapses upon deeper examination, revealing puzzles that silence traditional economics textbooks. Token economy micro-foundations raise three basic questions: How are tokens produced? What determines their value? What are they used for? These interconnected questions reveal transformed production methods leading to redefined value sources, emerging new enterprise organizations, and reconfigured centuries-old economic cells.
1. Production Puzzle: Whose Labor Creates Value? Imagine a fully automated smart restaurant with premium kitchen equipment (computing power) and global recipe databases (models). To eat, you must specify your meal and preferences (your prompt). Without your instruction, the finest kitchen remains idle. Token production requires three elements: models (vast knowledge/recipes), computing power (execution kitchen/energy), and prompts (user instructions). Crucially, prompt-providing users aren't "employees" of this AI restaurant—their ordering behavior is typically free. Yet billions of global users' free prompts continuously train and optimize the model. This resembles diners worldwide freely improving a restaurant's recipes while receiving no profit share, raising core production and distribution questions: Question 1: Are prompts labor? Is each AI query/conversation a new value-creating "digital labor"? If this massive global activity creates value, how should this "free labor" be regarded? Question 2: Do all labor participants receive distribution? Token value derives from model knowledge, computing execution, and user instructions. Do all contributing factors participate in value distribution? How is value from users' intangible prompt labor distributed—through improved free services or captured as platform profits? What criteria determine distribution fairness?
2. Pricing Puzzle: When Price Disconnects from Cost and Utility Using the restaurant metaphor, imagine each dish costs a fixed $1 processing fee—whether serving sliced cucumbers or a business plan saving your company. This reveals token pricing's fundamental contradiction: tokens represent standardized processing fees, but their utility ranges from trivial to priceless. Unlike electricity pricing tied to generation/transmission costs, token value varies immensely based on the instructed scenario upon production. Generating a joke versus a life-saving drug formula incurs identical costs but vastly different user value. Value locks at output, divorced from production costs, raising pricing mechanism questions: Question 3: What determines price? Should token value reflect the billions invested in model development or the minimal electricity consumed during generation? Can a commodity's value simultaneously derive from massive upfront investment and negligible marginal cost? Question 4: Are price signals still accurate? Token usage prices fall rapidly while certain production costs (e.g., high-end chips, energy) rise. When market prices lose stable connection to clear costs, can we still rely on price signals for economic decisions?
3. Organization Puzzle: The Collapse of Corporate "Walls" Traditional firms required clear boundaries—offices, production lines, employees—as economist Coase explained, existing where organizational costs undercut market transactions. Token economies rewrite these rules, erasing traditional firm boundaries. Accessing advanced intelligence becomes as easy and cheap as utilities. In many sectors, traditional organizational forms become unnecessary when key intelligent resources (large models) become easily accessible externally. Consequently, core competitiveness shifts toward abilities like discovering high-value applications or creative prompts—transitioning from "owning production materials" to "possessing valuable ideas." This transforms traditional understandings of firms, raising questions: Question 5: How will traditional firms evolve? Where should boundaries lie when buying external intelligence outperforms in-house development? Will "virtual companies" emerge—tiny teams leveraging external AI for all operations? Question 6: What new monopolies might form? If future winners excel at "asking questions," could monopolies arise over "high-value queries" or "AI mobilization methods"? What new challenges would this pose for competition and innovation?
II. Macro-Manifestations: Structural Characteristics and Consequences Token economy micro-features inevitably manifest as new systematic characteristics at macro levels. First, the token economy industrial system exhibits clear internal structure but follows entirely different supply-demand logics across segments. Second, understanding this structure's operation must help address new problems in measuring growth, adjusting distribution, and maintaining stable development.
1. Industrial System Puzzle: A "Three-Stage Rocket" The token economy resembles a spacecraft: bottom-level "fuel/engine" (computing power/energy), middle "control/navigation system" (large model platforms), and top "payload/satellites" (applications/agents). Each stage proves critical but operates differently. Foundational layers require massive general-purpose investment; middle layers face intense competition; application layers see massive demand. Unlike traditional linear value chains (e.g., auto manufacturing), token economies lack direct cost-value transmission between expensive foundational layers and cheap application layers. Computing chips grow costlier while token-based AI services become cheaper, raising industrial development questions: Question 1: Is this "three-stage" structure normal/sustainable? Could huge foundational costs ultimately limit innovation speed/scale in other layers? How to ensure foundational momentum supports entire system development? Question 2: How should nations allocate across stages? When building autonomous token economies, should strategic focus prioritize breakthrough core technologies at foundational layers or ensure diverse commercial success at application layers to pull foundational development?
2. Growth and Accounting Puzzle: Why Is Prosperity "Unclear"? This "economic rocket" elevates social efficiency/convenience, but traditional GDP measurements fail to capture much contribution. Traditional industrial/service growth reflects market sales captured by GDP. However, token economy value creation—free powerful translation tools, billions of hours saved via smart customer service, efficiency gains from AI-assisted programming/writing, expanded personal development opportunities—remains uncounted like household production/services. Only massive construction investments enter GDP, forcing reconsideration of economic progress metrics: Question 3: Are we using an old ruler for a new world? When significant value creation escapes traditional GDP accounting, does this system still reflect digital-era prosperity? Do we need supplementary systems to measure "silent prosperity"? Question 4: How to evaluate huge "new infrastructure" investments? Massive data/AI computing center investments boost current GDP as capital formation. But what are long-term returns? If supported applications' immense social value remains invisible under traditional frameworks, how should we assess long-term benefits to avoid decision biases?
3. Stability and Regulation Puzzle: Policy Dilemmas Under "Ice and Fire" Token economies simultaneously create opposing macroeconomic phenomena: "cost-reducing efficiency fire" from intelligent services versus "supply-constrained cost ice" from underlying resources. This challenges traditional macroeconomic policy thermostats. Service/consumption sides experience price declines from proliferating powerful AI, while production/supply sides face inflationary pressure from constrained computing resources. Previously, economic overheating/cooling showed uniformity allowing unified policy adjustment. Now, upstream resource cost pressures coexist with downstream technological price declines. AI service price drops benefit consumers/enterprises, but rising foundational computing costs challenge digital economy foundations. Policymakers risk misjudgment by observing only partial pictures, raising core economic governance questions: Question 5: Where should macroeconomic policy targets aim? When CPI remains stable from falling service prices, should policies address rapidly rising production factor prices (e.g., computing chips, elite talent)? Do we need finer policy tools for this "coexisting cold/heat" complexity? Question 6: How can growth benefits reach broader populations? Token economy growth rewards concentrate upstream and among elite talent. Through what specific mechanisms (e.g., factor income share changes, asset premiums, occupational polarization) will this affect overall income distribution? What blind spots might existing fiscal/social policies face addressing this new "technological inequality"?
III. Governance Restructuring: Adaptive Governance for "New Economic Foundations" When micro-level economic operations reshape and macro-level industrial landscapes transform, the "rules of the game" for managing economic systems require updating. Token economies present not just isolated policy challenges but holistic governance logic tests, forcing answers about governments' new roles, required tools, and adjusted domestic/international competition/cooperation rules. This section raises essential questions across governance objectives, policy tools, and supporting rule systems—answers determining whether we can steer intelligent revolution waves toward national long-term development and common welfare.
1. Governance Objectives: Can Efficiency and Equity Coexist? All governance requires objectives. Traditional economies prioritize growth and stability. Token economies present greater complexity: we must maximize this "intelligent engine" for national competitiveness while ensuring balanced "thrust" benefits broader populations rather than widening gaps. Thus: Question 1: For developing advanced productive forces, what should states do? What constitutes intelligent-era infrastructure like electricity/networks? Perhaps high-quality public data, inclusive computing power, and secure foundational models. Should states evolve from traditional industry supporters into primary planners/providers of such "new infrastructure"? Like national highway networks enabling logistics, should we build nationwide "public data resource networks" and "inclusive computing networks" ensuring fair access for all innovators rather than exclusion by private giants' walls? Question 2: How to integrate social equity into new strategies? When technological change may accelerate wealth concentration toward technology/capital, how can "fairly sharing development fruits among all people" substantively integrate into intelligent economy blueprints? What new mechanisms recognize/protect user/data contributor rights in value creation? Crucially, how establish long-term systematic arrangements channeling technological dividends continuously toward民生 fields?
2. Policy Tools: Old Tools Fail, Where Are New Ones? New objectives demand new tools. Familiar policy instruments—economic measurement statistics, anti-monopoly regulations, redistribution taxes—were designed for industrial-era economies. Facing token economy challenges like "unclear growth, new competition forms, transformation pains," old tools prove increasingly inadequate. Thus: Question 3: How to see real economic pictures? When massive AI-created social welfare (saved time, enhanced experiences) escapes traditional GDP, we navigate in fog. What new measurement systems should economists/statisticians develop to comprehensively reflect intelligent-era national welfare/economic vitality? This supplements rather than replaces GDP. Question 4: How to maintain healthy market competition? Past monopolies controlled output or raised prices. New monopolies may be subtler: controlling critical model interfaces making all applications dependent. How should anti-monopoly regulation upgrade to address technology-dependent/ecosystem-controlled market dominance beyond watching market share/prices? Question 5: How to tax/incentivize wisely? Taxes importantly adjust distribution. Intelligent economies concentrate value in data/algorithm application. How should tax system innovation reasonably capture digital-era value while avoiding innovation suppression? Can tax incentives guide capital toward long-term basic research rather than short-term arbitrage? Question 6: How to support human transformation beyond relief? Facing potential labor market structural changes, mere unemployment relief proves insufficient. How should education systems, vocational training networks, and social security institutions fundamentally reshape to help workers continuously adapt/learn new skills throughout lives, maintaining employment resilience/vitality?
3. Rule Systems: How to Legislate for the Future and Speak Globally? All governance objectives/tools require stable, clear rules for implementation—both domestic laws/regulations and international rules. Token economies outpace existing legislation and challenge old international orders. Thus: Question 7: How can domestic laws keep pace? When "virtual enterprises" proliferate, AI-generated content involves copyright, and data becomes core production factors, existing legal systems show gaps/ambiguities. What new foundational laws should we research/enact to clarify data/algorithm/computing power ownership/circulation rules? How update relevant laws适应 human-AI collaboration/AI creation modes, providing stable expectations for all market participants? Question 8: How can China help shape global rules? Issues like cross-border data flow, AI ethics standards, global digital tax coordination require multinational solutions. How can China more actively/constructively participate/lead global rule discussions/formation? How translate our large-scale market practices/experiences into international rule-making influence, creating fairer favorable external environments for national development?
From micro-level value/production puzzles through macro-level industrial restructuring/growth myths to governance-level objective/tool/rule questions, this token economy examination produces a weighty question list. Token economy emergence实质上 presents a new "economic foundation." History shows that when economic foundations transform significantly, corresponding "superstructures"—including cognitive systems, management methods, institutional arrangements—must adjust/innovate. All raised questions point toward this profound era命题. This article's purpose involves systematically sorting/posing these real new questions. They lack ready answers but mark clear exploration directions for future economic research, policy discussion, and institutional design. Answers won't emerge spontaneously—they'll gradually appear through sustained interdisciplinary research, open rational social debate, and prudent bold policy practice. Ultimately, whether we can build governance systems that both liberate intelligent productive forces and ensure development serves common people's interests will determine our ability to steer this historic transformation, turning technological waves into sustained momentum for national modernization and better lives. This intelligent-era development logic contemplation has only just begun.
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